{"id":108831,"date":"2025-08-21T02:55:45","date_gmt":"2025-08-21T02:55:45","guid":{"rendered":"https:\/\/www.dumpsbase.com\/freedumps\/?p=108831"},"modified":"2025-08-21T02:55:45","modified_gmt":"2025-08-21T02:55:45","slug":"share-more-aif-c01-free-dumps-part-2-q41-q70-the-aif-c01-dumps-v14-02-are-great-for-your-aws-certified-ai-practitioner-exam-preparation","status":"publish","type":"post","link":"https:\/\/www.dumpsbase.com\/freedumps\/share-more-aif-c01-free-dumps-part-2-q41-q70-the-aif-c01-dumps-v14-02-are-great-for-your-aws-certified-ai-practitioner-exam-preparation.html","title":{"rendered":"Share More AIF-C01 Free Dumps (Part 2, Q41-Q70): The AIF-C01 Dumps (V14.02) Are Great for Your AWS Certified AI Practitioner Exam Preparation"},"content":{"rendered":"<p>You can get the AIF-C01 dumps (V14.02) from DumpsBase to prepare for your AWS Certified AI Practitioner exam with confidence. Our AIF-C01 practice exam questions are designed to closely mimic the actual test, providing you with an authentic exam experience. From the <a href=\"https:\/\/www.dumpsbase.com\/freedumps\/aws-certified-ai-practitioner-aif-c01-dumps-updated-to-v14-02-for-your-preparation-try-to-test-the-quality-by-reading-aif-c01-free-dumps-part-1-q1-q40.html\"><em><strong>AIF-C01 free dumps (Part 1, Q1-Q40) of V14.02<\/strong><\/em><\/a>, you may find that our questions and answers are valuable for preparation. Our exam questions help you become familiar with the AWS Certified AI Practitioner test format, types of questions, and timing, which significantly reduces exam anxiety. Choose DumpsBase today, and take the first step towards advancing your career by investing in your AWS Certified AI Practitioner AIF-C01 exam preparation now. Furthermore, we will continue to share more free dumps online to help you check the V14.02 first.<\/p>\n<h2>Check <span style=\"background-color: #00ffff;\"><em>AIF-C01 free dumps (Part 2, Q41-Q70) of V14.02<\/em><\/span> online below:<\/h2>\n<script>\n\t  window.fbAsyncInit = function() {\n\t    FB.init({\n\t      appId            : '622169541470367',\n\t      autoLogAppEvents : true,\n\t      xfbml            : true,\n\t      version          : 'v3.1'\n\t    });\n\t  };\n\t\n\t  (function(d, s, id){\n\t     var js, fjs = d.getElementsByTagName(s)[0];\n\t     if (d.getElementById(id)) {return;}\n\t     js = d.createElement(s); js.id = id;\n\t     js.src = \"https:\/\/connect.facebook.net\/en_US\/sdk.js\";\n\t     fjs.parentNode.insertBefore(js, fjs);\n\t   }(document, 'script', 'facebook-jssdk'));\n\t<\/script><script type=\"text\/javascript\" >\ndocument.addEventListener(\"DOMContentLoaded\", function(event) { \nif(!window.jQuery) alert(\"The important jQuery library is not properly loaded in your site. Your WordPress theme is probably missing the essential wp_head() call. You can switch to another theme and you will see that the plugin works fine and this notice disappears. If you are still not sure what to do you can contact us for help.\");\n});\n<\/script>  \n  \n<div  id=\"watupro_quiz\" class=\"quiz-area single-page-quiz\">\n<p id=\"submittingExam10394\" style=\"display:none;text-align:center;\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/plugins\/watupro\/img\/loading.gif\" width=\"16\" height=\"16\"><\/p>\n\n<div class=\"watupro-exam-description\" id=\"description-quiz-10394\"><\/div>\n\n<form action=\"\" method=\"post\" class=\"quiz-form\" id=\"quiz-10394\"  enctype=\"multipart\/form-data\" >\n<div class='watu-question ' id='question-1' style=';'><div id='questionWrap-1'  class='   watupro-question-id-411833'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>1. <\/span>A company is building a chatbot to improve user experience. The company is using a large language model (LLM) from Amazon Bedrock for intent detection. The company wants to use few-shot learning to improve intent detection accuracy.<br \/>\r\n<br \/>\r\nWhich additional data does the company need to meet these requirements?<\/div><input type='hidden' name='question_id[]' id='qID_1' value='411833' \/><input type='hidden' id='answerType411833' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411833[]' id='answer-id-1596178' class='answer   answerof-411833 ' value='1596178'   \/><label for='answer-id-1596178' id='answer-label-1596178' class=' answer'><span>Pairs of chatbot responses and correct user intents<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411833[]' id='answer-id-1637841' class='answer   answerof-411833 ' value='1637841'   \/><label for='answer-id-1637841' id='answer-label-1637841' class=' answer'><span>Pairs of user messages and correct chatbot responses<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411833[]' id='answer-id-1637842' class='answer   answerof-411833 ' value='1637842'   \/><label for='answer-id-1637842' id='answer-label-1637842' class=' answer'><span>Pairs of user messages and correct user intents<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411833[]' id='answer-id-1637843' class='answer   answerof-411833 ' value='1637843'   \/><label for='answer-id-1637843' id='answer-label-1637843' class=' answer'><span>Pairs of user intents and correct chatbot responses<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-2' style=';'><div id='questionWrap-2'  class='   watupro-question-id-411834'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>2. <\/span>A company is building a large language model (LLM) question answering chatbot. The company wants to decrease the number of actions call center employees need to take to respond to customer questions.<br \/>\r\n<br \/>\r\nWhich business objective should the company use to evaluate the effect of the LLM chatbot?<\/div><input type='hidden' name='question_id[]' id='qID_2' value='411834' \/><input type='hidden' id='answerType411834' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411834[]' id='answer-id-1596179' class='answer   answerof-411834 ' value='1596179'   \/><label for='answer-id-1596179' id='answer-label-1596179' class=' answer'><span>Website engagement rate\r\n<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411834[]' id='answer-id-1637838' class='answer   answerof-411834 ' value='1637838'   \/><label for='answer-id-1637838' id='answer-label-1637838' class=' answer'><span>Average call duration<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411834[]' id='answer-id-1637839' class='answer   answerof-411834 ' value='1637839'   \/><label for='answer-id-1637839' id='answer-label-1637839' class=' answer'><span>Corporate social responsibility<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411834[]' id='answer-id-1637840' class='answer   answerof-411834 ' value='1637840'   \/><label for='answer-id-1637840' id='answer-label-1637840' class=' answer'><span>Regulatory compliance<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-3' style=';'><div id='questionWrap-3'  class='   watupro-question-id-411835'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>3. <\/span>A company is using few-shot prompting on a base model that is hosted on Amazon Bedrock. The model currently uses 10 examples in the prompt. The model is invoked once daily and is performing well. The company wants to lower the monthly cost.<br \/>\r\n<br \/>\r\nWhich solution will meet these requirements?<\/div><input type='hidden' name='question_id[]' id='qID_3' value='411835' \/><input type='hidden' id='answerType411835' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411835[]' id='answer-id-1596180' class='answer   answerof-411835 ' value='1596180'   \/><label for='answer-id-1596180' id='answer-label-1596180' class=' answer'><span>Customize the model by using fine-tuning.\r\n<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411835[]' id='answer-id-1637835' class='answer   answerof-411835 ' value='1637835'   \/><label for='answer-id-1637835' id='answer-label-1637835' class=' answer'><span>Decrease the number of tokens in the prompt.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411835[]' id='answer-id-1637836' class='answer   answerof-411835 ' value='1637836'   \/><label for='answer-id-1637836' id='answer-label-1637836' class=' answer'><span>Increase the number of tokens in the prompt.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411835[]' id='answer-id-1637837' class='answer   answerof-411835 ' value='1637837'   \/><label for='answer-id-1637837' id='answer-label-1637837' class=' answer'><span>Use Provisioned Throughput.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-4' style=';'><div id='questionWrap-4'  class='   watupro-question-id-411836'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>4. <\/span>An accounting firm wants to implement a large language model (LLM) to automate document processing. The firm must proceed responsibly to avoid potential harms.<br \/>\r\n<br \/>\r\nWhat should the firm do when developing and deploying the LLM? (Select TWO.)<\/div><input type='hidden' name='question_id[]' id='qID_4' value='411836' \/><input type='hidden' id='answerType411836' value='checkbox'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-411836[]' id='answer-id-1596181' class='answer   answerof-411836 ' value='1596181'   \/><label for='answer-id-1596181' id='answer-label-1596181' class=' answer'><span>Include fairness metrics for model evaluation.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-411836[]' id='answer-id-1637831' class='answer   answerof-411836 ' value='1637831'   \/><label for='answer-id-1637831' id='answer-label-1637831' class=' answer'><span>Adjust the temperature parameter of the model.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-411836[]' id='answer-id-1637832' class='answer   answerof-411836 ' value='1637832'   \/><label for='answer-id-1637832' id='answer-label-1637832' class=' answer'><span>Modify the training data to mitigate bias.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-411836[]' id='answer-id-1637833' class='answer   answerof-411836 ' value='1637833'   \/><label for='answer-id-1637833' id='answer-label-1637833' class=' answer'><span>Avoid overfitting on the training data.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-411836[]' id='answer-id-1637834' class='answer   answerof-411836 ' value='1637834'   \/><label for='answer-id-1637834' id='answer-label-1637834' class=' answer'><span>Apply prompt engineering techniques.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-5' style=';'><div id='questionWrap-5'  class='   watupro-question-id-411837'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>5. <\/span>A company has built an image classification model to predict plant diseases from photos of plant leaves. The company wants to evaluate how many images the model classified correctly. <br \/>\r<br>Which evaluation metric should the company use to measure the model's performance?<\/div><input type='hidden' name='question_id[]' id='qID_5' value='411837' \/><input type='hidden' id='answerType411837' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411837[]' id='answer-id-1596182' class='answer   answerof-411837 ' value='1596182'   \/><label for='answer-id-1596182' id='answer-label-1596182' class=' answer'><span>R-squared score<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411837[]' id='answer-id-1596183' class='answer   answerof-411837 ' value='1596183'   \/><label for='answer-id-1596183' id='answer-label-1596183' class=' answer'><span>Accuracy<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411837[]' id='answer-id-1596184' class='answer   answerof-411837 ' value='1596184'   \/><label for='answer-id-1596184' id='answer-label-1596184' class=' answer'><span>Root mean squared error (RMSE)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411837[]' id='answer-id-1596185' class='answer   answerof-411837 ' value='1596185'   \/><label for='answer-id-1596185' id='answer-label-1596185' class=' answer'><span>Learning rate<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-6' style=';'><div id='questionWrap-6'  class='   watupro-question-id-411838'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>6. <\/span>A large retailer receives thousands of customer support inquiries about products every day. The customer support inquiries need to be processed and responded to quickly. The company wants to implement Agents for Amazon Bedrock. <br \/>\r<br>What are the key benefits of using Amazon Bedrock agents that could help this retailer?<\/div><input type='hidden' name='question_id[]' id='qID_6' value='411838' \/><input type='hidden' id='answerType411838' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411838[]' id='answer-id-1596186' class='answer   answerof-411838 ' value='1596186'   \/><label for='answer-id-1596186' id='answer-label-1596186' class=' answer'><span>Generation of custom foundation models (FMs) to predict customer needs<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411838[]' id='answer-id-1596187' class='answer   answerof-411838 ' value='1596187'   \/><label for='answer-id-1596187' id='answer-label-1596187' class=' answer'><span>Automation of repetitive tasks and orchestration of complex workflows<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411838[]' id='answer-id-1596188' class='answer   answerof-411838 ' value='1596188'   \/><label for='answer-id-1596188' id='answer-label-1596188' class=' answer'><span>Automatically calling multiple foundation models (FMs) and consolidating the results<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411838[]' id='answer-id-1596189' class='answer   answerof-411838 ' value='1596189'   \/><label for='answer-id-1596189' id='answer-label-1596189' class=' answer'><span>Selecting the foundation model (FM) based on predefined criteria and metrics<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-7' style=';'><div id='questionWrap-7'  class='   watupro-question-id-411839'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>7. <\/span>A company is training a foundation model (FM). The company wants to increase the accuracy of the <br \/>\r<br>model up to a specific acceptance level. <br \/>\r<br>Which solution will meet these requirements?<\/div><input type='hidden' name='question_id[]' id='qID_7' value='411839' \/><input type='hidden' id='answerType411839' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411839[]' id='answer-id-1596190' class='answer   answerof-411839 ' value='1596190'   \/><label for='answer-id-1596190' id='answer-label-1596190' class=' answer'><span>Decrease the batch size.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411839[]' id='answer-id-1596191' class='answer   answerof-411839 ' value='1596191'   \/><label for='answer-id-1596191' id='answer-label-1596191' class=' answer'><span>Increase the epochs.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411839[]' id='answer-id-1596192' class='answer   answerof-411839 ' value='1596192'   \/><label for='answer-id-1596192' id='answer-label-1596192' class=' answer'><span>Decrease the epochs.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411839[]' id='answer-id-1596193' class='answer   answerof-411839 ' value='1596193'   \/><label for='answer-id-1596193' id='answer-label-1596193' class=' answer'><span>Increase the temperature parameter.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-8' style=';'><div id='questionWrap-8'  class='   watupro-question-id-411840'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>8. <\/span>A company has built a chatbot that can respond to natural language questions with images. The company wants to ensure that the chatbot does not return inappropriate or unwanted images. <br \/>\r<br>Which solution will meet these requirements?<\/div><input type='hidden' name='question_id[]' id='qID_8' value='411840' \/><input type='hidden' id='answerType411840' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411840[]' id='answer-id-1596194' class='answer   answerof-411840 ' value='1596194'   \/><label for='answer-id-1596194' id='answer-label-1596194' class=' answer'><span>Implement moderation APIs.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411840[]' id='answer-id-1596195' class='answer   answerof-411840 ' value='1596195'   \/><label for='answer-id-1596195' id='answer-label-1596195' class=' answer'><span>Retrain the model with a general public dataset.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411840[]' id='answer-id-1596196' class='answer   answerof-411840 ' value='1596196'   \/><label for='answer-id-1596196' id='answer-label-1596196' class=' answer'><span>Perform model validation.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411840[]' id='answer-id-1596197' class='answer   answerof-411840 ' value='1596197'   \/><label for='answer-id-1596197' id='answer-label-1596197' class=' answer'><span>Automate user feedback integration.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-9' style=';'><div id='questionWrap-9'  class='   watupro-question-id-411841'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>9. <\/span>A law firm wants to build an AI application by using large language models (LLMs). The application will read legal documents and extract key points from the documents. <br \/>\r<br>Which solution meets these requirements?<\/div><input type='hidden' name='question_id[]' id='qID_9' value='411841' \/><input type='hidden' id='answerType411841' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411841[]' id='answer-id-1596198' class='answer   answerof-411841 ' value='1596198'   \/><label for='answer-id-1596198' id='answer-label-1596198' class=' answer'><span>Build an automatic named entity recognition system.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411841[]' id='answer-id-1596199' class='answer   answerof-411841 ' value='1596199'   \/><label for='answer-id-1596199' id='answer-label-1596199' class=' answer'><span>Create a recommendation engine.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411841[]' id='answer-id-1596200' class='answer   answerof-411841 ' value='1596200'   \/><label for='answer-id-1596200' id='answer-label-1596200' class=' answer'><span>Develop a summarization chatbot.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411841[]' id='answer-id-1596201' class='answer   answerof-411841 ' value='1596201'   \/><label for='answer-id-1596201' id='answer-label-1596201' class=' answer'><span>Develop a multi-language translation system.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-10' style=';'><div id='questionWrap-10'  class='   watupro-question-id-411842'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>10. <\/span>A company wants to classify human genes into 20 categories based on gene characteristics. The company needs an ML algorithm to document how the inner mechanism of the model affects the output. <br \/>\r<br>Which ML algorithm meets these requirements?<\/div><input type='hidden' name='question_id[]' id='qID_10' value='411842' \/><input type='hidden' id='answerType411842' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411842[]' id='answer-id-1596202' class='answer   answerof-411842 ' value='1596202'   \/><label for='answer-id-1596202' id='answer-label-1596202' class=' answer'><span>Decision trees<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411842[]' id='answer-id-1596203' class='answer   answerof-411842 ' value='1596203'   \/><label for='answer-id-1596203' id='answer-label-1596203' class=' answer'><span>Linear regression<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411842[]' id='answer-id-1596204' class='answer   answerof-411842 ' value='1596204'   \/><label for='answer-id-1596204' id='answer-label-1596204' class=' answer'><span>Logistic regression<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411842[]' id='answer-id-1596205' class='answer   answerof-411842 ' value='1596205'   \/><label for='answer-id-1596205' id='answer-label-1596205' class=' answer'><span>Neural networks<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-11' style=';'><div id='questionWrap-11'  class='   watupro-question-id-411843'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>11. <\/span>A company wants to develop a large language model (LLM) application by using Amazon Bedrock and customer data that is uploaded to Amazon S3. The company's security policy states that each team can access data for only the team's own customers. <br \/>\r<br>Which solution will meet these requirements?<\/div><input type='hidden' name='question_id[]' id='qID_11' value='411843' \/><input type='hidden' id='answerType411843' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411843[]' id='answer-id-1596206' class='answer   answerof-411843 ' value='1596206'   \/><label for='answer-id-1596206' id='answer-label-1596206' class=' answer'><span>Create an Amazon Bedrock custom service role for each team that has access to only the team's customer data.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411843[]' id='answer-id-1596207' class='answer   answerof-411843 ' value='1596207'   \/><label for='answer-id-1596207' id='answer-label-1596207' class=' answer'><span>Create a custom service role that has Amazon S3 access. Ask teams to specify the customer name on each Amazon Bedrock request.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411843[]' id='answer-id-1596208' class='answer   answerof-411843 ' value='1596208'   \/><label for='answer-id-1596208' id='answer-label-1596208' class=' answer'><span>Redact personal data in Amazon S3. Update the S3 bucket policy to allow team access to customer data.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411843[]' id='answer-id-1596209' class='answer   answerof-411843 ' value='1596209'   \/><label for='answer-id-1596209' id='answer-label-1596209' class=' answer'><span>Create one Amazon Bedrock role that has full Amazon S3 access. Create IAM roles for each team that have access to only each team's customer folders.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-12' style=';'><div id='questionWrap-12'  class='   watupro-question-id-411844'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>12. <\/span>A company wants to use a large language model (LLM) on Amazon Bedrock for sentiment analysis.<br \/>\r\n<br \/>\r\nThe company wants to know how much information can fit into one prompt.<br \/>\r\n<br \/>\r\nWhich consideration will inform the company's decision?<\/div><input type='hidden' name='question_id[]' id='qID_12' value='411844' \/><input type='hidden' id='answerType411844' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411844[]' id='answer-id-1596210' class='answer   answerof-411844 ' value='1596210'   \/><label for='answer-id-1596210' id='answer-label-1596210' class=' answer'><span>Temperature\r\n<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411844[]' id='answer-id-1637828' class='answer   answerof-411844 ' value='1637828'   \/><label for='answer-id-1637828' id='answer-label-1637828' class=' answer'><span>Context window<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411844[]' id='answer-id-1637829' class='answer   answerof-411844 ' value='1637829'   \/><label for='answer-id-1637829' id='answer-label-1637829' class=' answer'><span>Batch size<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411844[]' id='answer-id-1637830' class='answer   answerof-411844 ' value='1637830'   \/><label for='answer-id-1637830' id='answer-label-1637830' class=' answer'><span>Model size<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-13' style=';'><div id='questionWrap-13'  class='   watupro-question-id-411845'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>13. <\/span>An AI practitioner has built a deep learning model to classify the types of materials in images. The AI practitioner now wants to measure the model performance. <br \/>\r<br>Which metric will help the AI practitioner evaluate the performance of the model?<\/div><input type='hidden' name='question_id[]' id='qID_13' value='411845' \/><input type='hidden' id='answerType411845' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411845[]' id='answer-id-1596211' class='answer   answerof-411845 ' value='1596211'   \/><label for='answer-id-1596211' id='answer-label-1596211' class=' answer'><span>Confusion matrix<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411845[]' id='answer-id-1596212' class='answer   answerof-411845 ' value='1596212'   \/><label for='answer-id-1596212' id='answer-label-1596212' class=' answer'><span>Correlation matrix<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411845[]' id='answer-id-1596213' class='answer   answerof-411845 ' value='1596213'   \/><label for='answer-id-1596213' id='answer-label-1596213' class=' answer'><span>R2 score<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411845[]' id='answer-id-1596214' class='answer   answerof-411845 ' value='1596214'   \/><label for='answer-id-1596214' id='answer-label-1596214' class=' answer'><span>Mean squared error (MSE)<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-14' style=';'><div id='questionWrap-14'  class='   watupro-question-id-411846'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>14. <\/span>An AI practitioner is building a model to generate images of humans in various professions. The AI practitioner discovered that the input data is biased and that specific attributes affect the image generation and create bias in the model. <br \/>\r<br>Which technique will solve the problem?<\/div><input type='hidden' name='question_id[]' id='qID_14' value='411846' \/><input type='hidden' id='answerType411846' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411846[]' id='answer-id-1596215' class='answer   answerof-411846 ' value='1596215'   \/><label for='answer-id-1596215' id='answer-label-1596215' class=' answer'><span>Data augmentation for imbalanced classes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411846[]' id='answer-id-1596216' class='answer   answerof-411846 ' value='1596216'   \/><label for='answer-id-1596216' id='answer-label-1596216' class=' answer'><span>Model monitoring for class distribution<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411846[]' id='answer-id-1596217' class='answer   answerof-411846 ' value='1596217'   \/><label for='answer-id-1596217' id='answer-label-1596217' class=' answer'><span>Retrieval Augmented Generation (RAG)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411846[]' id='answer-id-1596218' class='answer   answerof-411846 ' value='1596218'   \/><label for='answer-id-1596218' id='answer-label-1596218' class=' answer'><span>Watermark detection for images<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-15' style=';'><div id='questionWrap-15'  class='   watupro-question-id-411847'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>15. <\/span>A company is building an ML model to analyze archived data. The company must perform inference on large datasets that are multiple GBs in size. The company does not need to access the model predictions immediately. <br \/>\r<br>Which Amazon SageMaker inference option will meet these requirements?<\/div><input type='hidden' name='question_id[]' id='qID_15' value='411847' \/><input type='hidden' id='answerType411847' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411847[]' id='answer-id-1596219' class='answer   answerof-411847 ' value='1596219'   \/><label for='answer-id-1596219' id='answer-label-1596219' class=' answer'><span>Batch transform<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411847[]' id='answer-id-1596220' class='answer   answerof-411847 ' value='1596220'   \/><label for='answer-id-1596220' id='answer-label-1596220' class=' answer'><span>Real-time inference<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411847[]' id='answer-id-1596221' class='answer   answerof-411847 ' value='1596221'   \/><label for='answer-id-1596221' id='answer-label-1596221' class=' answer'><span>Serverless inference<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411847[]' id='answer-id-1596222' class='answer   answerof-411847 ' value='1596222'   \/><label for='answer-id-1596222' id='answer-label-1596222' class=' answer'><span>Asynchronous inference<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-16' style=';'><div id='questionWrap-16'  class='   watupro-question-id-411848'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>16. <\/span>A company needs to choose a model from Amazon Bedrock to use internally. The company must identify a model that generates responses in a style that the company's employees prefer. <br \/>\r<br>What should the company do to meet these requirements?<\/div><input type='hidden' name='question_id[]' id='qID_16' value='411848' \/><input type='hidden' id='answerType411848' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411848[]' id='answer-id-1596223' class='answer   answerof-411848 ' value='1596223'   \/><label for='answer-id-1596223' id='answer-label-1596223' class=' answer'><span>Evaluate the models by using built-in prompt datasets.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411848[]' id='answer-id-1596224' class='answer   answerof-411848 ' value='1596224'   \/><label for='answer-id-1596224' id='answer-label-1596224' class=' answer'><span>Evaluate the models by using a human workforce and custom prompt datasets.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411848[]' id='answer-id-1596225' class='answer   answerof-411848 ' value='1596225'   \/><label for='answer-id-1596225' id='answer-label-1596225' class=' answer'><span>Use public model leaderboards to identify the model.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411848[]' id='answer-id-1596226' class='answer   answerof-411848 ' value='1596226'   \/><label for='answer-id-1596226' id='answer-label-1596226' class=' answer'><span>Use the model InvocationLatency runtime metrics in Amazon CloudWatch when trying models.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-17' style=';'><div id='questionWrap-17'  class='   watupro-question-id-411849'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>17. <\/span>A company is using the Generative AI Security Scoping Matrix to assess security responsibilities for its solutions. The company has identified four different solution scopes based on the matrix. <br \/>\r<br>Which solution scope gives the company the MOST ownership of security responsibilities?<\/div><input type='hidden' name='question_id[]' id='qID_17' value='411849' \/><input type='hidden' id='answerType411849' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411849[]' id='answer-id-1596227' class='answer   answerof-411849 ' value='1596227'   \/><label for='answer-id-1596227' id='answer-label-1596227' class=' answer'><span>Using a third-party enterprise application that has embedded generative AI features.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411849[]' id='answer-id-1596228' class='answer   answerof-411849 ' value='1596228'   \/><label for='answer-id-1596228' id='answer-label-1596228' class=' answer'><span>Building an application by using an existing third-party generative AI foundation model (FM).<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411849[]' id='answer-id-1596229' class='answer   answerof-411849 ' value='1596229'   \/><label for='answer-id-1596229' id='answer-label-1596229' class=' answer'><span>Refining an existing third-party generative AI foundation model (FM) by fine-tuning the model by using data specific to the business.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411849[]' id='answer-id-1596230' class='answer   answerof-411849 ' value='1596230'   \/><label for='answer-id-1596230' id='answer-label-1596230' class=' answer'><span>Building and training a generative AI model from scratch by using specific data that a customer owns.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-18' style=';'><div id='questionWrap-18'  class='   watupro-question-id-411850'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>18. <\/span>A company uses Amazon SageMaker for its ML pipeline in a production environment. The company has large input data sizes up to 1 GB and processing times up to 1 hour. The company needs near real-time latency. <br \/>\r<br>Which SageMaker inference option meets these requirements?<\/div><input type='hidden' name='question_id[]' id='qID_18' value='411850' \/><input type='hidden' id='answerType411850' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411850[]' id='answer-id-1596231' class='answer   answerof-411850 ' value='1596231'   \/><label for='answer-id-1596231' id='answer-label-1596231' class=' answer'><span>Real-time inference<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411850[]' id='answer-id-1596232' class='answer   answerof-411850 ' value='1596232'   \/><label for='answer-id-1596232' id='answer-label-1596232' class=' answer'><span>Serverless inference<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411850[]' id='answer-id-1596233' class='answer   answerof-411850 ' value='1596233'   \/><label for='answer-id-1596233' id='answer-label-1596233' class=' answer'><span>Asynchronous inference<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411850[]' id='answer-id-1596234' class='answer   answerof-411850 ' value='1596234'   \/><label for='answer-id-1596234' id='answer-label-1596234' class=' answer'><span>Batch transform<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-19' style=';'><div id='questionWrap-19'  class='   watupro-question-id-411851'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>19. <\/span>A company wants to use language models to create an application for inference on edge devices. The inference must have the lowest latency possible. <br \/>\r<br>Which solution will meet these requirements?<\/div><input type='hidden' name='question_id[]' id='qID_19' value='411851' \/><input type='hidden' id='answerType411851' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411851[]' id='answer-id-1596235' class='answer   answerof-411851 ' value='1596235'   \/><label for='answer-id-1596235' id='answer-label-1596235' class=' answer'><span>Deploy optimized small language models (SLMs) on edge devices.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411851[]' id='answer-id-1596236' class='answer   answerof-411851 ' value='1596236'   \/><label for='answer-id-1596236' id='answer-label-1596236' class=' answer'><span>Deploy optimized large language models (LLMs) on edge devices.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411851[]' id='answer-id-1596237' class='answer   answerof-411851 ' value='1596237'   \/><label for='answer-id-1596237' id='answer-label-1596237' class=' answer'><span>Incorporate a centralized small language model (SLM) API for asynchronous communication with edge devices.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411851[]' id='answer-id-1596238' class='answer   answerof-411851 ' value='1596238'   \/><label for='answer-id-1596238' id='answer-label-1596238' class=' answer'><span>Incorporate a centralized large language model (LLM) API for asynchronous communication with edge devices.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-20' style=';'><div id='questionWrap-20'  class='   watupro-question-id-411852'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>20. <\/span>A company is building a contact center application and wants to gain insights from customer conversations. The company wants to analyze and extract key information from the audio of the customer calls.<br \/>\r\n<br \/>\r\nWhich solution meets these requirements?<\/div><input type='hidden' name='question_id[]' id='qID_20' value='411852' \/><input type='hidden' id='answerType411852' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411852[]' id='answer-id-1596239' class='answer   answerof-411852 ' value='1596239'   \/><label for='answer-id-1596239' id='answer-label-1596239' class=' answer'><span>Build a conversational chatbot by using Amazon Lex.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411852[]' id='answer-id-1637825' class='answer   answerof-411852 ' value='1637825'   \/><label for='answer-id-1637825' id='answer-label-1637825' class=' answer'><span>Transcribe call recordings by using Amazon Transcribe.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411852[]' id='answer-id-1637826' class='answer   answerof-411852 ' value='1637826'   \/><label for='answer-id-1637826' id='answer-label-1637826' class=' answer'><span>Extract information from call recordings by using Amazon SageMaker Model Monitor.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411852[]' id='answer-id-1637827' class='answer   answerof-411852 ' value='1637827'   \/><label for='answer-id-1637827' id='answer-label-1637827' class=' answer'><span>Create classification labels by using Amazon Comprehend.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-21' style=';'><div id='questionWrap-21'  class='   watupro-question-id-411853'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>21. <\/span>A company wants to build an ML model by using Amazon SageMaker. The company needs to share and manage variables for model development across multiple teams. <br \/>\r<br>Which SageMaker feature meets these requirements?<\/div><input type='hidden' name='question_id[]' id='qID_21' value='411853' \/><input type='hidden' id='answerType411853' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411853[]' id='answer-id-1596240' class='answer   answerof-411853 ' value='1596240'   \/><label for='answer-id-1596240' id='answer-label-1596240' class=' answer'><span>Amazon SageMaker Feature Store<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411853[]' id='answer-id-1596241' class='answer   answerof-411853 ' value='1596241'   \/><label for='answer-id-1596241' id='answer-label-1596241' class=' answer'><span>Amazon SageMaker Data Wrangler<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411853[]' id='answer-id-1596242' class='answer   answerof-411853 ' value='1596242'   \/><label for='answer-id-1596242' id='answer-label-1596242' class=' answer'><span>Amazon SageMaker Clarify<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411853[]' id='answer-id-1596243' class='answer   answerof-411853 ' value='1596243'   \/><label for='answer-id-1596243' id='answer-label-1596243' class=' answer'><span>Amazon SageMaker Model Cards<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-22' style=';'><div id='questionWrap-22'  class='   watupro-question-id-411854'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>22. <\/span>A company is using a pre-trained large language model (LLM) to build a chatbot for product recommendations. The company needs the LLM outputs to be short and written in a specific language. <br \/>\r<br>Which solution will align the LLM response quality with the company's expectations?<\/div><input type='hidden' name='question_id[]' id='qID_22' value='411854' \/><input type='hidden' id='answerType411854' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411854[]' id='answer-id-1596244' class='answer   answerof-411854 ' value='1596244'   \/><label for='answer-id-1596244' id='answer-label-1596244' class=' answer'><span>Adjust the prompt.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411854[]' id='answer-id-1596245' class='answer   answerof-411854 ' value='1596245'   \/><label for='answer-id-1596245' id='answer-label-1596245' class=' answer'><span>Choose an LLM of a different size.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411854[]' id='answer-id-1596246' class='answer   answerof-411854 ' value='1596246'   \/><label for='answer-id-1596246' id='answer-label-1596246' class=' answer'><span>Increase the temperature.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411854[]' id='answer-id-1596247' class='answer   answerof-411854 ' value='1596247'   \/><label for='answer-id-1596247' id='answer-label-1596247' class=' answer'><span>Increase the Top K value.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-23' style=';'><div id='questionWrap-23'  class='   watupro-question-id-411855'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>23. <\/span>A company uses a foundation model (FM) from Amazon Bedrock for an AI search tool. The company wants to fine-tune the model to be more accurate by using the company's data. <br \/>\r<br>Which strategy will successfully fine-tune the model?<\/div><input type='hidden' name='question_id[]' id='qID_23' value='411855' \/><input type='hidden' id='answerType411855' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411855[]' id='answer-id-1596248' class='answer   answerof-411855 ' value='1596248'   \/><label for='answer-id-1596248' id='answer-label-1596248' class=' answer'><span>Provide labeled data with the prompt field and the completion field.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411855[]' id='answer-id-1596249' class='answer   answerof-411855 ' value='1596249'   \/><label for='answer-id-1596249' id='answer-label-1596249' class=' answer'><span>Prepare the training dataset by creating a .txt file that contains multiple lines in .csv format.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411855[]' id='answer-id-1596250' class='answer   answerof-411855 ' value='1596250'   \/><label for='answer-id-1596250' id='answer-label-1596250' class=' answer'><span>Purchase Provisioned Throughput for Amazon Bedrock.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411855[]' id='answer-id-1596251' class='answer   answerof-411855 ' value='1596251'   \/><label for='answer-id-1596251' id='answer-label-1596251' class=' answer'><span>Train the model on journals and textbooks.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-24' style=';'><div id='questionWrap-24'  class='   watupro-question-id-411856'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>24. <\/span>An AI practitioner has a database of animal photos. The AI practitioner wants to automatically identify and categorize the animals in the photos without manual human effort. <br \/>\r<br>Which strategy meets these requirements?<\/div><input type='hidden' name='question_id[]' id='qID_24' value='411856' \/><input type='hidden' id='answerType411856' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411856[]' id='answer-id-1596252' class='answer   answerof-411856 ' value='1596252'   \/><label for='answer-id-1596252' id='answer-label-1596252' class=' answer'><span>Object detection<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411856[]' id='answer-id-1596253' class='answer   answerof-411856 ' value='1596253'   \/><label for='answer-id-1596253' id='answer-label-1596253' class=' answer'><span>Anomaly detection<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411856[]' id='answer-id-1596254' class='answer   answerof-411856 ' value='1596254'   \/><label for='answer-id-1596254' id='answer-label-1596254' class=' answer'><span>Named entity recognition<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411856[]' id='answer-id-1596255' class='answer   answerof-411856 ' value='1596255'   \/><label for='answer-id-1596255' id='answer-label-1596255' class=' answer'><span>Inpainting<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-25' style=';'><div id='questionWrap-25'  class='   watupro-question-id-411857'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>25. <\/span>A research company implemented a chatbot by using a foundation model (FM) from Amazon Bedrock. The chatbot searches for answers to questions from a large database of research papers. After multiple prompt engineering attempts, the company notices that the FM is performing poorly because of the complex scientific terms in the research papers. <br \/>\r<br>How can the company improve the performance of the chatbot?<\/div><input type='hidden' name='question_id[]' id='qID_25' value='411857' \/><input type='hidden' id='answerType411857' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411857[]' id='answer-id-1596256' class='answer   answerof-411857 ' value='1596256'   \/><label for='answer-id-1596256' id='answer-label-1596256' class=' answer'><span>Use few-shot prompting to define how the FM can answer the questions.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411857[]' id='answer-id-1596257' class='answer   answerof-411857 ' value='1596257'   \/><label for='answer-id-1596257' id='answer-label-1596257' class=' answer'><span>Use domain adaptation fine-tuning to adapt the FM to complex scientific terms.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411857[]' id='answer-id-1596258' class='answer   answerof-411857 ' value='1596258'   \/><label for='answer-id-1596258' id='answer-label-1596258' class=' answer'><span>Change the FM inference parameters.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411857[]' id='answer-id-1596259' class='answer   answerof-411857 ' value='1596259'   \/><label for='answer-id-1596259' id='answer-label-1596259' class=' answer'><span>Clean the research paper data to remove complex scientific terms.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-26' style=';'><div id='questionWrap-26'  class='   watupro-question-id-411858'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>26. <\/span>A medical company deployed a disease detection model on Amazon Bedrock. To comply with privacy policies, the company wants to prevent the model from including personal patient information in its responses. The company also wants to receive notification when policy violations occur. <br \/>\r<br>Which solution meets these requirements?<\/div><input type='hidden' name='question_id[]' id='qID_26' value='411858' \/><input type='hidden' id='answerType411858' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411858[]' id='answer-id-1596260' class='answer   answerof-411858 ' value='1596260'   \/><label for='answer-id-1596260' id='answer-label-1596260' class=' answer'><span>Use Amazon Macie to scan the model's output for sensitive data and set up alerts for potential violations.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411858[]' id='answer-id-1596261' class='answer   answerof-411858 ' value='1596261'   \/><label for='answer-id-1596261' id='answer-label-1596261' class=' answer'><span>Configure AWS CloudTrail to monitor the model's responses and create alerts for any detected personal information.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411858[]' id='answer-id-1596262' class='answer   answerof-411858 ' value='1596262'   \/><label for='answer-id-1596262' id='answer-label-1596262' class=' answer'><span>Use Guardrails for Amazon Bedrock to filter content. Set up Amazon CloudWatch alarms for notification of policy violations.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411858[]' id='answer-id-1596263' class='answer   answerof-411858 ' value='1596263'   \/><label for='answer-id-1596263' id='answer-label-1596263' class=' answer'><span>Implement Amazon SageMaker Model Monitor to detect data drift and receive alerts when model quality degrades.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-27' style=';'><div id='questionWrap-27'  class='   watupro-question-id-411859'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>27. <\/span>An education provider is building a question and answer application that uses a generative AI model to explain complex concepts. The education provider wants to automatically change the style of the model response depending on who is asking the question. The education provider will give the model the age range of the user who has asked the question. <br \/>\r<br>Which solution meets these requirements with the LEAST implementation effort?<\/div><input type='hidden' name='question_id[]' id='qID_27' value='411859' \/><input type='hidden' id='answerType411859' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411859[]' id='answer-id-1596264' class='answer   answerof-411859 ' value='1596264'   \/><label for='answer-id-1596264' id='answer-label-1596264' class=' answer'><span>Fine-tune the model by using additional training data that is representative of the various age ranges that the application will support.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411859[]' id='answer-id-1596265' class='answer   answerof-411859 ' value='1596265'   \/><label for='answer-id-1596265' id='answer-label-1596265' class=' answer'><span>Add a role description to the prompt context that instructs the model of the age range that the response should target.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411859[]' id='answer-id-1596266' class='answer   answerof-411859 ' value='1596266'   \/><label for='answer-id-1596266' id='answer-label-1596266' class=' answer'><span>Use chain-of-thought reasoning to deduce the correct style and complexity for a response suitable for that user.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411859[]' id='answer-id-1596267' class='answer   answerof-411859 ' value='1596267'   \/><label for='answer-id-1596267' id='answer-label-1596267' class=' answer'><span>Summarize the response text depending on the age of the user so that younger users receive shorter responses.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-28' style=';'><div id='questionWrap-28'  class='   watupro-question-id-411860'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>28. <\/span>A social media company wants to use a large language model (LLM) for content moderation. The company wants to evaluate the LLM outputs for bias and potential discrimination against specific groups or individuals. <br \/>\r<br>Which data source should the company use to evaluate the LLM outputs with the LEAST administrative effort?<\/div><input type='hidden' name='question_id[]' id='qID_28' value='411860' \/><input type='hidden' id='answerType411860' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411860[]' id='answer-id-1596268' class='answer   answerof-411860 ' value='1596268'   \/><label for='answer-id-1596268' id='answer-label-1596268' class=' answer'><span>User-generated content<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411860[]' id='answer-id-1596269' class='answer   answerof-411860 ' value='1596269'   \/><label for='answer-id-1596269' id='answer-label-1596269' class=' answer'><span>Moderation logs<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411860[]' id='answer-id-1596270' class='answer   answerof-411860 ' value='1596270'   \/><label for='answer-id-1596270' id='answer-label-1596270' class=' answer'><span>Content moderation guidelines<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411860[]' id='answer-id-1596271' class='answer   answerof-411860 ' value='1596271'   \/><label for='answer-id-1596271' id='answer-label-1596271' class=' answer'><span>Benchmark datasets<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-29' style=';'><div id='questionWrap-29'  class='   watupro-question-id-411861'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>29. <\/span>Which strategy evaluates the accuracy of a foundation model (FM) that is used in image classification tasks?<\/div><input type='hidden' name='question_id[]' id='qID_29' value='411861' \/><input type='hidden' id='answerType411861' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411861[]' id='answer-id-1596272' class='answer   answerof-411861 ' value='1596272'   \/><label for='answer-id-1596272' id='answer-label-1596272' class=' answer'><span>Calculate the total cost of resources used by the model.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411861[]' id='answer-id-1637844' class='answer   answerof-411861 ' value='1637844'   \/><label for='answer-id-1637844' id='answer-label-1637844' class=' answer'><span>Measure the model's accuracy against a predefined benchmark dataset.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411861[]' id='answer-id-1637845' class='answer   answerof-411861 ' value='1637845'   \/><label for='answer-id-1637845' id='answer-label-1637845' class=' answer'><span>Count the number of layers in the neural network.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411861[]' id='answer-id-1637846' class='answer   answerof-411861 ' value='1637846'   \/><label for='answer-id-1637846' id='answer-label-1637846' class=' answer'><span>Assess the color accuracy of images processed by the model.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-30' style=';'><div id='questionWrap-30'  class='   watupro-question-id-411862'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>30. <\/span>A company has terabytes of data in a database that the company can use for business analysis. The company wants to build an AI-based application that can build a SQL query from input text that employees provide. The employees have minimal experience with technology. <br \/>\r<br>Which solution meets these requirements?<\/div><input type='hidden' name='question_id[]' id='qID_30' value='411862' \/><input type='hidden' id='answerType411862' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411862[]' id='answer-id-1596273' class='answer   answerof-411862 ' value='1596273'   \/><label for='answer-id-1596273' id='answer-label-1596273' class=' answer'><span>Generative pre-trained transformers (GPT)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411862[]' id='answer-id-1596274' class='answer   answerof-411862 ' value='1596274'   \/><label for='answer-id-1596274' id='answer-label-1596274' class=' answer'><span>Residual neural network<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411862[]' id='answer-id-1596275' class='answer   answerof-411862 ' value='1596275'   \/><label for='answer-id-1596275' id='answer-label-1596275' class=' answer'><span>Support vector machine<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-411862[]' id='answer-id-1596276' class='answer   answerof-411862 ' value='1596276'   \/><label for='answer-id-1596276' id='answer-label-1596276' class=' answer'><span>WaveNet<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div style='display:none' id='question-31'>\n\t<div class='question-content'>\n\t\t<img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/plugins\/watupro\/img\/loading.gif\" width=\"16\" height=\"16\" alt=\"Loading...\" title=\"Loading...\" \/>&nbsp;Loading...\t<\/div>\n<\/div>\n\n<br \/>\n\t\n\t\t\t<div class=\"watupro_buttons flex \" id=\"watuPROButtons10394\" >\n\t\t  <div id=\"prev-question\" style=\"display:none;\"><input type=\"button\" value=\"&lt; 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   \t \n<\/script>\n","protected":false},"excerpt":{"rendered":"<p>You can get the AIF-C01 dumps (V14.02) from DumpsBase to prepare for your AWS Certified AI Practitioner exam with confidence. Our AIF-C01 practice exam questions are designed to closely mimic the actual test, providing you with an authentic exam experience. From the AIF-C01 free dumps (Part 1, Q1-Q40) of V14.02, you may find that our [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[175,17613],"tags":[19590,19591],"class_list":["post-108831","post","type-post","status-publish","format-standard","hentry","category-amazon","category-aws-certified-ai-practitioner","tag-aif-c01-practice-exam-questions","tag-aws-certified-ai-practitioner-aif-c01-exam"],"_links":{"self":[{"href":"https:\/\/www.dumpsbase.com\/freedumps\/wp-json\/wp\/v2\/posts\/108831","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.dumpsbase.com\/freedumps\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.dumpsbase.com\/freedumps\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.dumpsbase.com\/freedumps\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.dumpsbase.com\/freedumps\/wp-json\/wp\/v2\/comments?post=108831"}],"version-history":[{"count":1,"href":"https:\/\/www.dumpsbase.com\/freedumps\/wp-json\/wp\/v2\/posts\/108831\/revisions"}],"predecessor-version":[{"id":108832,"href":"https:\/\/www.dumpsbase.com\/freedumps\/wp-json\/wp\/v2\/posts\/108831\/revisions\/108832"}],"wp:attachment":[{"href":"https:\/\/www.dumpsbase.com\/freedumps\/wp-json\/wp\/v2\/media?parent=108831"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.dumpsbase.com\/freedumps\/wp-json\/wp\/v2\/categories?post=108831"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.dumpsbase.com\/freedumps\/wp-json\/wp\/v2\/tags?post=108831"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}